Square root {RandomFields}R Documentation

Methods relying on square roots of the covariance matrix

Description

Methods relying on square roots of the covariance matrix

Usage

RPdirect(phi, boxcox) 

Arguments

phi

object of class RMmodel; specifies the covariance model to be simulated.

boxcox

the one or two parameters of the box cox transformation. If not given, the globally defined parameters are used. See RFboxcox for details.

Details

RPdirect is based on the well-known method for simulating any multivariate Gaussian distribution, using the square root of the covariance matrix. The method is pretty slow and limited to about 12000 points, i.e. a 20x20x20 grid in three dimensions. This implementation can use the Cholesky decomposition and the singular value decomposition. It allows for arbitrary points and arbitrary grids.

Value

RPdirect returns an object of class RMmodel.

Author(s)

Martin Schlather, schlather@math.uni-mannheim.de, https://www.wim.uni-mannheim.de/schlather/

References

See Also

Gaussian, RP, RPsequential.

Examples

RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
##                   RFoptions(seed=NA) to make them all random again
model <- RMgauss(var=10, s=10) + RMnugget(var=0.01)
plot(model, xlim=c(-25, 25))

z <- RFsimulate(model=RPdirect(model), 0:10, 0:10, n=4)
plot(z)


[Package RandomFields version 3.3.13 Index]